Expert systems for the control of plants and processing facilities are well known. Such systems include a "shell" that contains the general software architecture and structure that would apply, for example, to any nuclear plant.
Such a system also includes a plant-specific knowledge base. The knowledge base contains the information that describes the design and operation of a specific plant. The knowledge base is stored in memory accessed under the control of the shell to produce a plant-specific expert system. The traditional Al approach to structuring a diagnostic knowledge base is to encode the knowledge in a set of statements or "production rules" of the form: "If A, then B." This approach works in those cases where out knowledge of the system has this absolute, syllogistic character. However, for systems about which our knowledge is uncertain and for which we must reason in terms of levels of confidence, this approach is inadequate. Attempts to graft provisions for uncertainty onto rule-based approaches have proved to be inadequate. The current invention includes, and is inherently built around, a complete and accurate treatment of uncertainty.